Wind forcing plays a pivotal role in driving upper-ocean physical and biogeochemical processes, yet direct wind observations remain sparse in many regions of the global ocean. While passive acoustics have been used to estimate wind speed from moored and mobile platforms, their application to profiling floats has been demonstrated only in limited cases. Here we report the first deployment of a biogeochemical profiling float equipped with a passive acoustic sensor explicitly designed for wind retrieval, aimed at detecting wind-driven surface signals from depth. The float was deployed in the northwestern Mediterranean Sea near the DYFAMED (DYnamique des Flux Atmosph & eacute;riques en MEDiterran & eacute;e) meteorological buoy from February to April 2025 and operated at parking depths of 500-1000 m. We demonstrate that wind speed can be successfully retrieved from subsurface ambient noise using established acoustic algorithms, with float-derived estimates showing good agreement with collocated surface observations. To evaluate scalability to remote regions, we simulate a remote deployment scenario by refitting the acoustic model of Nystuen et al. (2015) using ERA5 reanalysis as a reference for surface wind. The ERA5-based calibration performs well under moderate winds but exhibits systematic high-wind bias (>= 10 m s-1). Finally, we apply a residual learning framework to correct these estimates using a limited subset of DYFAMED wind data, simulating conditions where only brief surface observations are available. The corrected wind time series achieved a 38.6 % reduction in RMSE, demonstrating the effectiveness of combining reanalysis with sparse in-situ calibration. This framework improves agreement with in-situ wind observations relative to reanalysis alone, supporting a scalable strategy for float-based wind monitoring in data-sparse ocean regions. Such capability has direct implications for improving estimates of air-sea exchanges, interpreting biogeochemical fluxes, and advancing climate-relevant ocean observing.

Passive acoustic monitoring from profiling floats as a pathway to scalable autonomous observations of global surface wind

Pensieri S.
Writing – Original Draft Preparation
;
Bozzano R.
Writing – Original Draft Preparation
;
2026

Abstract

Wind forcing plays a pivotal role in driving upper-ocean physical and biogeochemical processes, yet direct wind observations remain sparse in many regions of the global ocean. While passive acoustics have been used to estimate wind speed from moored and mobile platforms, their application to profiling floats has been demonstrated only in limited cases. Here we report the first deployment of a biogeochemical profiling float equipped with a passive acoustic sensor explicitly designed for wind retrieval, aimed at detecting wind-driven surface signals from depth. The float was deployed in the northwestern Mediterranean Sea near the DYFAMED (DYnamique des Flux Atmosph & eacute;riques en MEDiterran & eacute;e) meteorological buoy from February to April 2025 and operated at parking depths of 500-1000 m. We demonstrate that wind speed can be successfully retrieved from subsurface ambient noise using established acoustic algorithms, with float-derived estimates showing good agreement with collocated surface observations. To evaluate scalability to remote regions, we simulate a remote deployment scenario by refitting the acoustic model of Nystuen et al. (2015) using ERA5 reanalysis as a reference for surface wind. The ERA5-based calibration performs well under moderate winds but exhibits systematic high-wind bias (>= 10 m s-1). Finally, we apply a residual learning framework to correct these estimates using a limited subset of DYFAMED wind data, simulating conditions where only brief surface observations are available. The corrected wind time series achieved a 38.6 % reduction in RMSE, demonstrating the effectiveness of combining reanalysis with sparse in-situ calibration. This framework improves agreement with in-situ wind observations relative to reanalysis alone, supporting a scalable strategy for float-based wind monitoring in data-sparse ocean regions. Such capability has direct implications for improving estimates of air-sea exchanges, interpreting biogeochemical fluxes, and advancing climate-relevant ocean observing.
2026
Istituto per lo studio degli impatti Antropici e Sostenibilità in ambiente marino - IAS - Genova
Acoustic meteorology; passive acoustic; wind
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/568781
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